Natural Disaster Application on Big Data and Machine Learning: A Review

Arinta, Rania Rizki and Emanuel, Andi Wahju Rahardjo (2019) Natural Disaster Application on Big Data and Machine Learning: A Review. In: Proceedings 2019 4th International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE). UNIVERSITAS AMIKOM YOGYAKARTA, pp. 1-6. ISBN 978-1-7281-5118-2

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Abstract

Natural disasters are events that are difficult to avoid. There are several ways of reducing the risks of natural disasters. One of them is implementing disaster reduction programs. There are already several developed countries that apply the concept of disaster reduction. In addition to disaster reduction programs, there are several ways to predict or reducing the risks using artificial intelligence technology. One of them is big data, machine learning, and deep learning. By utilizing this method at the moment, it facilitates tasks in visualizing, analyzing, and predicting natural disaster. This research will focus on conducting a review process and understanding the purpose of machine learning and big data in the area of disaster management and natural disaster. The result of this paper is providing insight and the use of big data, machine learning, and deep learning in 6 disaster management area. This 6-disaster management area includes early warning damage, damage assessment, monitoring and detection, forecasting and predicting, and post-disaster coordination, and response, and long-term risk assessment and reduction.

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